scatter plot and hexbin plot lose x-axis when colorbar is included. (#20446)

Author: javadnoorb

doc/source/whatsnew/v0.24.0.txt

@@ -336,7 +336,7 @@ I/O
 Plotting
 ^^^^^^^^
 
--
+- Bug in :func:'DataFrame.plot.scatter' and :func:'DataFrame.plot.hexbin' caused x-axis label and ticklabels to disappear when colorbar was on in IPython inline backend (:issue:`10611` and :issue:`10678`)
 -
 -
 

pandas/plotting/_core.py

@@ -833,6 +833,32 @@ def _post_plot_logic(self, ax, data):
         ax.set_ylabel(pprint_thing(y))
         ax.set_xlabel(pprint_thing(x))
 
+    def _plot_colorbar(self, ax, **kwds):
+        # Addresses issues #10611 and #10678:
+        # When plotting scatterplots and hexbinplots in IPython
+        # inline backend the colorbar axis height tends not to
+        # exactly match the parent axis height.
+        # The difference is due to small fractional differences
+        # in floating points with similar representation.
+        # To deal with this, this method forces the colorbar
+        # height to take the height of the parent axes.
+        # For a more detailed description of the issue
+        # see the following link:
+        # https://github.com/ipython/ipython/issues/11215
+
+        img = ax.collections[0]
+        cbar = self.fig.colorbar(img, **kwds)
+        points = ax.get_position().get_points()
+        cbar_points = cbar.ax.get_position().get_points()
+        cbar.ax.set_position([cbar_points[0, 0],
+                              points[0, 1],
+                              cbar_points[1, 0] - cbar_points[0, 0],
+                              points[1, 1] - points[0, 1]])
+        # To see the discrepancy in axis heights uncomment
+        # the following two lines:
+        # print(points[1, 1] - points[0, 1])
+        # print(cbar_points[1, 1] - cbar_points[0, 1])
+
 
 class ScatterPlot(PlanePlot):
     _kind = 'scatter'
@@ -878,11 +904,9 @@ def _make_plot(self):
         scatter = ax.scatter(data[x].values, data[y].values, c=c_values,
                              label=label, cmap=cmap, **self.kwds)
         if cb:
-            img = ax.collections[0]
-            kws = dict(ax=ax)
             if self.mpl_ge_1_3_1():
-                kws['label'] = c if c_is_column else ''
-            self.fig.colorbar(img, **kws)
+                cbar_label = c if c_is_column else ''
+            self._plot_colorbar(ax, label=cbar_label)
 
         if label is not None:
             self._add_legend_handle(scatter, label)
@@ -923,8 +947,7 @@ def _make_plot(self):
         ax.hexbin(data[x].values, data[y].values, C=c_values, cmap=cmap,
                   **self.kwds)
         if cb:
-            img = ax.collections[0]
-            self.fig.colorbar(img, ax=ax)
+            self._plot_colorbar(ax)
 
     def _make_legend(self):
         pass

pandas/tests/plotting/test_frame.py

@@ -1089,6 +1089,49 @@ def test_plot_scatter(self):
         axes = df.plot(x='x', y='y', kind='scatter', subplots=True)
         self._check_axes_shape(axes, axes_num=1, layout=(1, 1))
 
+    @pytest.mark.slow
+    def test_if_scatterplot_colorbar_affects_xaxis_visibility(self):
+        # addressing issue #10611, to ensure colobar does not
+        # interfere with x-axis label and ticklabels with
+        # ipython inline backend.
+        random_array = np.random.random((1000, 3))
+        df = pd.DataFrame(random_array,
+                          columns=['A label', 'B label', 'C label'])
+
+        ax1 = df.plot.scatter(x='A label', y='B label')
+        ax2 = df.plot.scatter(x='A label', y='B label', c='C label')
+
+        vis1 = [vis.get_visible() for vis in
+                ax1.xaxis.get_minorticklabels()]
+        vis2 = [vis.get_visible() for vis in
+                ax2.xaxis.get_minorticklabels()]
+        assert vis1 == vis2
+
+        vis1 = [vis.get_visible() for vis in
+                ax1.xaxis.get_majorticklabels()]
+        vis2 = [vis.get_visible() for vis in
+                ax2.xaxis.get_majorticklabels()]
+        assert vis1 == vis2
+
+        assert (ax1.xaxis.get_label().get_visible() ==
+                ax2.xaxis.get_label().get_visible())
+
+    @pytest.mark.slow
+    def test_if_hexbin_xaxis_label_is_visible(self):
+        # addressing issue #10678, to ensure colobar does not
+        # interfere with x-axis label and ticklabels with
+        # ipython inline backend.
+        random_array = np.random.random((1000, 3))
+        df = pd.DataFrame(random_array,
+                          columns=['A label', 'B label', 'C label'])
+
+        ax = df.plot.hexbin('A label', 'B label', gridsize=12)
+        assert all([vis.get_visible() for vis in
+                    ax.xaxis.get_minorticklabels()])
+        assert all([vis.get_visible() for vis in
+                    ax.xaxis.get_majorticklabels()])
+        assert ax.xaxis.get_label().get_visible()
+
     @pytest.mark.slow
     def test_plot_scatter_with_categorical_data(self):
         # GH 16199